For Underwater Vehicle Manipulator Systems (UVMS), the ability to keep a fixed end effector pose is required for intervention tasks. Maintaining a static configuration in a dynamic underwater environment requires significant amounts of energy over time, limiting the operational time for battery powered systems. In this work we consider learning the periodic components of the dynamic flow in order to generate periodic trajectories which keep the end effector fixed, yet minimise the energy expenditure over time. We compare this proposed ‘go with the flow’ approach to the static configuration case for a fixed end effector pose, and show a significant reduction in energy use.